Satyen Kale (Google Research)
Date: Friday, October 2, 2020
Time: 1:30 PM – 2:30 PM (CDT; UTC -5)
Location: Online (Zoom link will be provided)
Meeting Time: 11:00 AM – 12:00 PM Central (CDT; UTC -5)
The application of supervised learning techniques for the design of the physical layer of a communication link is often impaired by the limited amount of pilot data available for each device; while the use of unsupervised learning is typically limited by the need to carry out a large number of training iterations. In this talk, meta-learning, or learning-to-learn, is introduced as a tool to alleviate these problems. The talk will consider an Internet-of-Things (IoT) scenario in which devices transmit sporadically using short packets with few pilot symbols over a fading channel.